bachelor-thesis/typstalt/sources.bib

%! Author = lukas
%! Date = 4/9/24

@InProceedings{crossentropy,
    ISSN = {00359246},
    URL = {http://www.jstor.org/stable/2984087},
    abstract = {This paper deals first with the relationship between the theory of probability and the theory of rational behaviour. A method is then suggested for encouraging people to make accurate probability estimates, a connection with the theory of information being mentioned. Finally Wald's theory of statistical decision functions is summarised and generalised and its relation to the theory of rational behaviour is discussed.},
    author = {I. J. Good},
    journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
    number = {1},
    pages = {107--114},
    publisher = {[Royal Statistical Society, Wiley]},
    title = {Rational Decisions},
    urldate = {2024-05-23},
    volume = {14},
    year = {1952}
}

@misc{efficientADpaper,
    title={EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies},
    author={Kilian Batzner and Lars Heckler and Rebecca König},
    year={2024},
    eprint={2303.14535},
    archivePrefix={arXiv},
    primaryClass={cs.CV},
    url={https://arxiv.org/abs/2303.14535},
}

@misc{patchcorepaper,
    title={Towards Total Recall in Industrial Anomaly Detection},
    author={Karsten Roth and Latha Pemula and Joaquin Zepeda and Bernhard Schölkopf and Thomas Brox and Peter Gehler},
    year={2022},
    eprint={2106.08265},
    archivePrefix={arXiv},
    primaryClass={cs.CV},
    url={https://arxiv.org/abs/2106.08265},
}

@misc{jupyter,
	    author = {},
	    title = {{Project Jupyter Documentation}},
	    howpublished = "\url{https://docs.jupyter.org/en/latest/}",
	    year = {2024},
	    note = "[Online; accessed 13-May-2024]"
}

@misc{cnnintro,
    title={An Introduction to Convolutional Neural Networks},
    author={Keiron O'Shea and Ryan Nash},
    year={2015},
    eprint={1511.08458},
    archivePrefix={arXiv},
    primaryClass={cs.NE}
}

@misc{cnnarchitectureimg,
    author = {},
    title = {{What are convolutional neural networks?}},
    howpublished = "\url{https://cointelegraph.com/explained/what-are-convolutional-neural-networks}",
    year = {2024},
    note = "[Online; accessed 12-April-2024]"
}

@misc{datasetsampleimg,
    author = {},
    title = {{The MVTec anomaly detection dataset (MVTec AD)}},
    howpublished = "\url{https://www.mvtec.com/company/research/datasets/mvtec-ad}",
    year = {2024},
    note = "[Online; accessed 12-April-2024]"
}

@inproceedings{liang2017soft,
    title={Soft-margin softmax for deep classification},
    author={Liang, Xuezhi and Wang, Xiaobo and Lei, Zhen and Liao, Shengcai and Li, Stan Z},
    booktitle={International Conference on Neural Information Processing},
    pages={413--421},
    year={2017},
    organization={Springer}
}

@inbook{Boltzmann,
	    place = {Cambridge},
    series = {Cambridge Library Collection - Physical  Sciences},
	    title = {Studien über das Gleichgewicht der lebendigen Kraft zwischen bewegten materiellen Punkten},
	    booktitle = {Wissenschaftliche Abhandlungen},
	    publisher = {Cambridge University Press},
	    author = {Boltzmann, Ludwig},
	    editor = {Hasenöhrl, FriedrichEditor},
	    year = {2012},
    pages = {49–96},
    collection = {Cambridge Library Collection - Physical  Sciences}, key = {value},}

@misc{resnet,
    title={Deep Residual Learning for Image Recognition},
    author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
    year={2015},
    eprint={1512.03385},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}